{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nes_py.wrappers import JoypadSpace\n",
    "import gym_super_mario_bros\n",
    "from gym_super_mario_bros.actions import SIMPLE_MOVEMENT\n",
    "import time\n",
    "from matplotlib import pyplot as plt\n",
    "from gym.wrappers import GrayScaleObservation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "env = gym_super_mario_bros.make('SuperMarioBros-v0')\n",
    "env = JoypadSpace(env, SIMPLE_MOVEMENT)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一、打印原图片"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(240, 256, 3)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x26abafbef40>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "state = env.reset()\n",
    "print(state.shape)\n",
    "plt.imshow(state)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 二、打印灰度图图片"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "del env\n",
    "env = gym_super_mario_bros.make('SuperMarioBros-v0')\n",
    "env = JoypadSpace(env, SIMPLE_MOVEMENT)\n",
    "env = GrayScaleObservation(env,keep_dim=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(240, 256, 1)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x26abb0e8a00>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PN7Ip8RMAbjz4Lb7M2IxJObch/UBodc9pRE9A6VTRA13u9/+6lG5P/ReXjux8Cu/RFAKOW0jd1E7qpnYaltnIu3qbZ/CeWW90KyZ9+fOH25j2j0XgUgg+YiFup4LSLs9f9wZZ6sI7dIWgIxZMNng354/DnlzLHVcSXK7i8gf7vY1MfDmcat94lfFlRbZQhNdoVij8h+eHPR2TorLj6aexh+oc+uG56fmfsGJqlt/MS0kKirjkoj62ELPL1O3LP1yRpiAO37MegO8m5dGcbEJ1wLgyBbVNisqlIktaXFIT3zNRt7yLgEDbiMV4LOwY2qp3GW/q4KVfLMfcpmAPHrFw4jxSUMQlFbq/jmf+40/M9bOMaJz/E34UgJdGNIq4kOzyiEvq8A9j+dn3VtOmdY14rOStD9Aeq2KP7PmCdTEypKCIS8oV5qD87/z4zg3fAaDC0cb3ji0cUNuzV8oOxOR37ye0RKF1mgPMck3KpSIFRVxyur+LQ09Ec8eC5Uwwmbk/+hMerp6HQ3fxg6rr+OSCjReH7qLAZuPluhtYN6Gg2zCX3nuxKF/yIp1R7utS5LL8S0cKivAOs0bxY9F8a/n9LAzQuHF8Cdd++Xd8UZfAgwV3s99m54yrg5PONq76LIu7v7yX4oZoflxzPWdcHZ5u0aG7sOk9H2NgUlQOPfg8/g06lgY5VHipyJIW3qOCY7wfz51JBODFmX9kjp+VH1Rdx+NlK2hoDULXFaLGtREf3MSamI94/NAK5h93P/YiLLiDN2e8ip8S1GPS+212Pu1IoetvmnGclsdjXCqyhSK8Rvd3cfx2C29l3cBbWTdw96bH2Nlp4oX4z/ho5v+SHlvNrNgadlzxP4Rb27nRH34+PYcromu5IrqWTWmbiDK5i8l3K24GoNjewTfLb+O7m3/EW1k34CwM9eIcXn4UoPcnIF1ChQ013JmzydtpCC8LKbbSFaHDlHbeue55ki3B2HQH03MfIPoDC413drB0ajG/nZjnaTNn/wpa2/2J3ezPybu7cJ4KIPHPLhqvsNIyw+7FuRk7ts+61fPM6P7ILo/wGa1pdkKKrQQVBXL7kZ/gsoKiw4RD0JChE5UTyMcTMpgaf42nTXgRRDh0TtyhEZMTiG28wrFvuwApJt4gBUX4lNY0O61p7q0VUxfoKjQscBeH2lvAcspCyLFzZ20arnWCRft6uJwe9jYpKMIntab1voXhiHTQFHmJkxEDJgdlhRCGkYIihDCMFBQhhGGkoAghDCMFRQhhGCkoQgjDSEERQhhGCooQwjBSUIQQhpGCIoQwjBQUIYRhpKAIIQwjBUUIYRgpKEIIw0hBEUIYRgqKEMIwUlCEEIaRgiKEMIwUFCGEYaSgCCEMIwVFCGGYfgvKhg0bqKur4+DBg55+YWFh5ObmUlpaSm5uLqGhoZ5hzz77LGVlZRQWFpKenj4iSQshfFO/BeWVV15h6dKl3fqtXbuWnTt3kpqays6dO1m7di0Ay5YtIyUlhZSUFNasWcP69etHJmshhE/qt6Ds3r2bxsbGbv0yMzPZuHEjABs3bmT58uWe/ps2uV8punfvXkJDQ4mJiTE4ZSGErxrSMZTo6Ghqa2sBqK2tJTo6GoC4uDgqKys941VVVREXF9frNFavXk1eXh55eXmE+wcOJQ0hhI8x5KCsrg/+fevZ2dlkZGSQkZFBY1eHEWkIIbxsSAWlrq7OsysTExNDfX09ANXV1SQkJHjGi4+Pp7q62oA0hRCjwZAKSk5ODllZWQBkZWWxY8cOT/9Vq1YBMG/ePJqbmz27RkKIsa/fl6Vv2bKFhQsXEhkZSWVlJevWreOpp55i27Zt3HfffRw/fpwVK1YA8Pbbb3P77bdTXl5OR0cH99xzz4jPgBDCdyjA4A+AGKywoYY7czZ5Ow0hRC+2z7qVjIyMAY0rV8oKIQwjBUUIYRgpKEIIw0hBEUIYRgqKEMIwUlCEEIaRgiKEMIwUFCGEYaSgCCEMIwVFCGEYKShCCMNIQRFCGEYKihDCMFJQhBCGkYIihDCMFBQhhGGkoAghDCMFRQhhGCkoQgjDSEERQhhGCooQwjBSUIQQhpGCIoQwjBQUIYRhpKAIIQwjBUUIYRgpKEIIw0hBEUIYRgqKEMIwUlCEEIaRgiKEMIwUFCGEYaSgCCEMIwVFCGEYKShCCMNIQRFCGKbfgrJhwwbq6uo4ePCgp9+6deuoqqoiPz+f/Px8li1b5hm2du1aysrKKCkpYfHixSOTtRDCJ/VbUF555RWWLl3ao/8zzzxDeno66enpvPPOOwCkpaWxcuVKZsyYwdKlS3n++edRVdkIEuJy0e+3fffu3TQ2Ng5oYpmZmWzduhW73c6xY8coLy9n7ty5w05SCDE6DHnz4eGHH6awsJANGzYQGhoKQFxcHJWVlZ5xqqqqiIuLG3aSQojRYUgFZf369SQnJzN79mxOnjzJ008/PehprF69mry8PPLy8gj3DxxKGkIIHzOkglJfX4+maei6TnZ2tme3prq6moSEBM948fHxVFdX9zqN7OxsMjIyyMjIoLGrYyhpCCF8zJAKSkxMjOf/d911F0VFRQDk5OSwcuVKrFYrSUlJpKSksG/fPmMyFUL4PHN/I2zZsoWFCxcSGRlJZWUl69atY+HChcyePRtd1zl27Bg/+MEPADh06BDbtm3j0KFDOJ1OHnroITRNG/GZEEL4BgXQvZ1EYUMNd+Zs8nYaQohebJ91KxkZGQMaVy4SEUIYRgqKEMIwUlCEEIaRgiKEMIwUFCGEYaSgCCEMIwVFCGEYKShCCMNIQRFCGEYKihDCMFJQhBCGkYIihDCMFBQhhGGkoAghDCMFRQhhmH4fsHS5iNxjYcL2r7r3NJko/s9k7yQkxCh0+RYUl4K5yUzyz/a7P14/g6rVM7uPo8O0H37h/v/saRy+39/9SCrV68+kEsInXZYFRekwMW3tQdTx4zjx2DUXHbf6sWtAh5BKjek/PkDznbM4ebMGZnm0pRAXuuwKivm0hdTnTnDiodkDa6BDSJVG2OfV1Nwzm/FHHUTuM3MqA7BIURHifJfVQVn/KitTtzRRuSJxwG1MdgjZ+jnO45VEf97M6ZkWQk7YCc83geOyWnxC9Ouy+UYEHrESv6uTkzeFoZuGN62GdD/GH7UTuc8EzstmEQrRr8vi2xBUZmVCgYNTMwNw+Q2szYRCO9FfdPU5vCHdj6BaJxM/VEFXDMpUiNFtzBeUwCNWIg86aEky4xzEG0/99hRj+igfzQyORXMwRUdxZsa4buOcnmlBdeokvS5nfYSAMV5QAo5bidlnoznJgiN4aFsRuglOX+lHwx3JdET3nEZTsonOSDNTX3EON10hRr0xW1AsDRYmvdtKY5ofzqDhTUszQ1dE3wWpfaJK89QAUl52DC+QEKPcmDxtrLaZSck+SdXfTESzDG0aNfdfhTKIPZnOSAVFCyR5s40jd4/ZOi3ERY29Nd+uMu1fSjnxzaEXEwDNyoAP4AKgQEe0QkeUlUk7VNDkQK24/IypgqJ0mEj7aRmV9053XyLvBa2T3Is0+hM5pSwuP2NmjTefspD2XyepvC/N26nQON1MYL2T8C+lqIjLy5hY2/2rrCT/qYWqu+K9tmVyoYarrISW2wkrkKIiLh+jfk0PqLAS93EXddeNR/OxQ8z1c/wIK/v6ilqXj1Q6IUbQqC4ogUesROU7aJzuhzPA29n0rv5qP4JOOpn4gVxRK8Y+H/tNH7iACvfl9C2J5gFftBad18WpWf6DO3szAHG7Wqi+eVyfw0/PtBB6xEXS6zrHvm1sbOFbwvZbCDts93w++h0VTAO4/sClMOW1c3evN6b50ZRuv0gDA2KOgFFZUPyqrUz8tIvG6X6DKibmz74iriKKyr9NGNwNggo9dqcUFygaJOTU4yo9QkJnKpW3R/Q5iaZkE8HVClNftVH+98O8O1H4pPGFVmyhULnm3AWO036tcfgB/37bTnupi6OPn1uXLYV+jDtopeXKixeV4cQcCaOuoJgbLST9bzN188cPajfH2tCOy2bDebwSRU9gwPVbAZeFHgd7z+691CyJIrr0CPqJGqDvggLQNlHFZfFn6qtdUlTGEL8aC8kvnqD6m4lcv7yQeP8znmG7fplK2iNdFP8ktNe209Z3Yqprov1lC3dHl3r6n0gK58tXZxFUZqU9pWdRGU7MkTSqjqEonSZSf1/FyYWDKybDoStgD9Wxj9fpnGIn6sYaOifbMWecQTfDxFeLQR9geVKgc4JCa7wfk7fKDYVjganJTPwuGzGvN7Mwa1+3LzbAvAnH4GQ95lOWHrdmpL5oo36dk5jXm7n5vGICMCmgEV11P49n+u86UFvO/fYPJ+ZI67egxMfH8+GHH/LVV19RVFTEo48+CkBYWBi5ubmUlpaSm5tLaGiop82zzz5LWVkZhYWFpKenG5OpQ2X6P5Vw4tsJAz6bE3JCY+KvPyPyoAPd9PUmhTq4LYPOWI3IGQ24xjmZmliHn8mJYtIxKTrxN1Zi+1MIqr8/inmASSnue3/soWbi3jXJFbWjna6gODQmBTQSZu7oNsimmQlU7YS+YyL5tRaOPqSSuF3x/M3VLgfjA7qYFNDYrZ2GgkM38Y37dhNUo1G1Dqa9cAql0zTsmCOt34LidDp5/PHHmTFjBtdeey0PPfQQaWlprF27lp07d5KamsrOnTtZu3YtAMuWLSMlJYWUlBTWrFnD+vXrh52k0mEi7WflVK6eMfjrTHQddJ2qJeGYUqZQ/8N5gz697NJUlC4TR2siAUiMO0XTyXE0dgTg0lTOvBFP5f2Du6CuebIJc7tG5GdmuU5ltNIVTDawh1oBaHP50WAPwfb1Crb97fnU2MYzLbiO617J5+9n7qVysYmYXSYUmwlXiD9m1X0gtsEewmmH+y7WT+qnsqVgLg7dxJInP+FbUwqYt+0Q0548NKyYl0K/a3JtbS35+fkAtLW1UVxcTFxcHJmZmWzcuBGAjRs3snz5cgAyMzPZtGk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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "state = env.reset()\n",
    "print(state.shape)\n",
    "plt.imshow(state)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "184320\n",
      "61440\n"
     ]
    }
   ],
   "source": [
    "print(240*256*3)\n",
    "print(240*256)"
   ]
  }
 ],
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